Improved PESA algorithm based on comentropy
Aiming at the issue that the computational effort the complexity and the running time of PESA algorithm are increasing rapidly with the growth of the solutions set number, a comentropy-based PESA algorithm (C-PESA) by merg-ing the entropy value metric into PESA algorithm was proposed. According to t...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2013-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.11.005/ |
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| _version_ | 1850123291531935744 |
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| author | Kun WANG Lin-lin WANG Yan LIU Yu-hua ZHANG Meng WU |
| author_facet | Kun WANG Lin-lin WANG Yan LIU Yu-hua ZHANG Meng WU |
| author_sort | Kun WANG |
| collection | DOAJ |
| description | Aiming at the issue that the computational effort the complexity and the running time of PESA algorithm are increasing rapidly with the growth of the solutions set number, a comentropy-based PESA algorithm (C-PESA) by merg-ing the entropy value metric into PESA algorithm was proposed. According to the distributed characteristic of the entropy value metric over the Pareto solution set, the proposed algorithm could determine whether the population has developed to the mature stage, which is reached when the number iterations is 1 300 in C-PESA. Thereby, the optimization process can be finished as soon as possible, and in a certain extent, the time complexity of PESA was simplified. Simula-tion results show that the computational effort of C-PESA increases linearly with the rising number of solutions. Mean-while, the computation time is improved almost four times, and the evolutionary computation efficiency is also enhanced. |
| format | Article |
| id | doaj-art-682b35620fdd43ea9324c72dfafcbcd3 |
| institution | OA Journals |
| issn | 1000-436X |
| language | zho |
| publishDate | 2013-11-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-682b35620fdd43ea9324c72dfafcbcd32025-08-20T02:34:39ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2013-11-0134334159834442Improved PESA algorithm based on comentropyKun WANGLin-lin WANGYan LIUYu-hua ZHANGMeng WUAiming at the issue that the computational effort the complexity and the running time of PESA algorithm are increasing rapidly with the growth of the solutions set number, a comentropy-based PESA algorithm (C-PESA) by merg-ing the entropy value metric into PESA algorithm was proposed. According to the distributed characteristic of the entropy value metric over the Pareto solution set, the proposed algorithm could determine whether the population has developed to the mature stage, which is reached when the number iterations is 1 300 in C-PESA. Thereby, the optimization process can be finished as soon as possible, and in a certain extent, the time complexity of PESA was simplified. Simula-tion results show that the computational effort of C-PESA increases linearly with the rising number of solutions. Mean-while, the computation time is improved almost four times, and the evolutionary computation efficiency is also enhanced.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.11.005/evolutionary computationPESA algorithmmulti-objective optimizationcomentropy |
| spellingShingle | Kun WANG Lin-lin WANG Yan LIU Yu-hua ZHANG Meng WU Improved PESA algorithm based on comentropy Tongxin xuebao evolutionary computation PESA algorithm multi-objective optimization comentropy |
| title | Improved PESA algorithm based on comentropy |
| title_full | Improved PESA algorithm based on comentropy |
| title_fullStr | Improved PESA algorithm based on comentropy |
| title_full_unstemmed | Improved PESA algorithm based on comentropy |
| title_short | Improved PESA algorithm based on comentropy |
| title_sort | improved pesa algorithm based on comentropy |
| topic | evolutionary computation PESA algorithm multi-objective optimization comentropy |
| url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.11.005/ |
| work_keys_str_mv | AT kunwang improvedpesaalgorithmbasedoncomentropy AT linlinwang improvedpesaalgorithmbasedoncomentropy AT yanliu improvedpesaalgorithmbasedoncomentropy AT yuhuazhang improvedpesaalgorithmbasedoncomentropy AT mengwu improvedpesaalgorithmbasedoncomentropy |